Residential and commercial real estate are the world's two largest tangible asset classes. Residential real estate accounts for the bulk of the average household's wealth portfolio. Understanding the pattern of price movements in residential and commercial real estate is therefore of vital importance to households, policy-makers, regulators, businesses and investors. Historically, accurate measures of the time-series changes in the risk and return characteristics of residential and commercial real estate assets have been extremely hard to come by. In turn, the valuation of individual property assets using automated and/or statistical property valuation systems has been a hazardous practice. Finally, the development of financial derivative and futures contracts based on proxies for the residential and commercial real estate asset class have been hindered by poor index design.
The present specification is primarily concerned with two core areas: 11 (1) unique data collection methods and processing systems for quantifying, measuring, evaluating and ultimately outputting estimates of time-series risk and return movements in residential and commercial real estate portfolios; and, 11 (2) unique data collection methods and processing systems for quantifying, measuring, evaluating and ultimately outputting estimates of the values of various derivative financial instruments that enable capital markets participants to secure synthetic investment exposures to residential and commercial property assets, or to synthetically hedge against the risk inherent in the ownership of such assets, amongst other things.
In reviewing the background art, two key areas of focus are: (1) the extant evidence surrounding the development of property indices; and (2) the extant evidence on the use of index-linked property derivatives and other types of financial contracts;
1. Data processing, evaluation, and index-output systems
Historically, there has been a great deal of public criticism from economists, commentators, regulators and policymakers about the integrity of the existing sources of property price performance.
Ian Macfarlane, the former Governor of the Reserve Bank of Australia said:
“Housing . . . is an extremely important asset class for most people, yet the information we have on prices is hopeless compared with the information we have on share prices, bond prices, and foreign exchange rates . . . . It really is probably the weakest link in all the price data in the country so I think it is something that I would like to see resources put into.”
The criticism has a common basis: that the dynamics of the price performance measures do not accurately reflect the dynamics of the true property values, for a combination of three possible reasons:                i. The sample of property sales used to construct the measures is insufficient or biased,        ii. The sample of property sales used to construct the measures is obtained a significant time after the actual transactions have occurred and thus the measures represent past, not present conditions, and        iii. The statistical measures calculated from the sample of property sales are not accurate or meaningful representations of changes in value of the population of properties from which the sample is taken.        